Skip to main content

Advertisement

SpringerLink
Log in

Identification and deformation analysis of potential landslides after the Jiuzhaigou earthquake by SBAS-InSAR

  • Research Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

A World Natural Heritage Site, Jiuzhaigou, is the first nature reserve in China whose primary purpose is to protect natural scenery. On August 8, 2017, a Ms 7.0 earthquake caused many unstable slopes in Jiuzhaigou, Sichuan Province, China. In the extreme storm conditions that follow, the unstable slopes tend to develop into potential landslides, which can cause many casualties and property losses in scenic areas. Sentinel-1A ascending orbit data were obtained in this paper to establish a SAR database. The large-scale deformation rate map of the study area was obtained using a small baseline set InSAR technology. The potential landslides in the deformation area are preliminarily confirmed with remote sensing interpretation. The field verification is further carried out by studying the deformation information of the characteristic points on the potential landslides. The results show that 13 deformation zones were preliminarily identified, and three typical deformation zones were selected for coupling verification and identified as potential landslides. At the same time, further analysis shows that the four potential landslides have been in continuous linear deformation for a long time since the earthquake, posing a severe threat to the safety of local people’s lives and property. The research results provide a reference for the early identification and warning of potential landslides in earthquake-prone regions.

Graphical Abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Data availability

All data generated or analyzed during this study are included in this published article.

References

  • Bamler R, Eineder M (2005) Accuracy of differential shift estimation by correlation and split-bandwidth interferometry for wideband and deltas SAR systems. IEEE Geosci Remote Sens Lett 2:151–155. https://doi.org/10.1109/Lgrs.2004.843203

    Article  Google Scholar 

  • Bayer B, Schmidt D, Simoni A (2017) The influence of external digital elevation models on ps-Insar and SBAS results: implications for the analysis of deformation signals caused by slow-moving landslides in the northern Apennines (Italy). IEEE Trans Geosci Remote Sens 55:2618–2631. https://doi.org/10.1109/Tgrs.2017.2648885

    Article  Google Scholar 

  • Behling R, Roessner S, Golovko D, Kleinschmit B (2016) Derivation of long-term spatiotemporal landslide activity-a multi-sensor time series approach. Remote Sens Environ 186:88–104. https://doi.org/10.1016/j.rse.2016.07.017

    Article  Google Scholar 

  • Berardino P, Fornaro G, Lanari R, Sansosti E (2002) A new algorithm for surface deformation monitoring based on small baseline differential sar interferograms. IEEE Trans Geosci Remote Sens 40:2375–2383. https://doi.org/10.1109/Tgrs.2002.803792

    Article  Google Scholar 

  • Bovenga F, Belmonte A, Refice A, Pasquariello G, Nutricato R, Nitti DO, Chiaradia MT (2018) Performance analysis of satellite missions for multi-temporal sar interferometry. Sensors-Basel 18:1359. https://doi.org/10.3390/s18051359

    Article  Google Scholar 

  • Chang M, Tang C, Xia C, Fang Q (2016) Spatial distribution analysis of landslides triggered by the 2013–04-20 Lushan earthquake, china. Earthq Eng Eng Vib 15:163–171. https://doi.org/10.1007/s11803-016-0313-5

    Article  Google Scholar 

  • Chang ZQ, Yu W, Wang W, Zhang JF, Liu XM, Zhu J (2017) An approach for accurately retrieving the vertical deformation component from two-track InSAR measurements. Int J Remote Sens 38:1702–1719. https://doi.org/10.1080/01431161.2017.1285448

    Article  Google Scholar 

  • Colesanti C, Ferretti A, Novali F, Prati C, Rocca F (2003) Sar monitoring of progressive and seasonal ground deformation using the permanent scatterers technique. IEEE Trans Geosci Remote Sens 41:1685–1701. https://doi.org/10.1109/Tgrs.2003.813278

    Article  Google Scholar 

  • Dong J, Zhang L, Tang MG, Liao MS, Xu Q, Gong JY, Ao M (2018) Mapping landslide surface displacements with time series SAR interferometry by combining persistent and distributed scatterers: a case study of Jiaju landslides in Danba, china. Remote Sens Environ 205:180–198. https://doi.org/10.1016/j.rse.2017.11.022

    Article  Google Scholar 

  • Fattahi H, Amelung F (2013) Dem error correction in insar time series. IEEE Trans Geosci Remote Sens 51:4249–4259. https://doi.org/10.1109/Tgrs.2012.2227761

    Article  Google Scholar 

  • Ferretti A, Monti-Guarnieri AV, Prati CM, Rocca F and Massonnet D (2007) Insar principles b. ESA publications

  • Guo R, Li SM, Chen YN, Li XX, Yuan LW (2021) Identification and monitoring landslides in the longitudinal range-gorge region with InSAR fusion integrated visibility analysis. Landslides 18:551–568. https://doi.org/10.1007/s10346-020-01475-7

    Article  Google Scholar 

  • Hong SY, Zhou X, Zhang K, Meng GJ, Dong YF, Su XN, Zhang L, Li S and Ding KL (2018) Source model and stress disturbance of the 2017 Jiuzhaigou MW 6.5 earthquake constrained by InSAR and GPS measurements. Remote Sens-Basel 10. https://doi.org/10.3390/rs10091400

  • Hu X, Wang T, Pierson TC, Lu Z, Kim J, Cecere TH (2016) Detecting seasonal landslide movement within the cascade landslide complex (Washington) using time-series SAR imagery. Remote Sens Environ 187:49–61. https://doi.org/10.1016/j.rse.2016.10.006

    Article  Google Scholar 

  • Intrieri E, Gigli G, Mugnai F, Fanti R, Casagli N (2012) Design and implementation of a landslide early warning system. Eng Geol 147:124–136. https://doi.org/10.1016/j.enggeo.2012.07.017

    Article  Google Scholar 

  • Jolivet R, Agram PS, Lin NNY, Simons M, Doin MP, Peltzer G, Li ZH (2014) Improving InSAR geodesy using global atmospheric models. J Geophys Res-Sol Ea 119:2324–2341. https://doi.org/10.1002/2013jb010588

    Article  Google Scholar 

  • Keefer DK, Wilson RC, Mark RK, Brabb EE, Brown WM, Ellen SD, Harp EL, Wieczorek GF, Alger CS, Zatkin RS (1987) Real-time landslide warning during heavy rainfall. Science 238:921–925. https://doi.org/10.1126/science.238.4829.921

    Article  CAS  Google Scholar 

  • Li ZB, Shi WZ, Lu P, Yan L, Wang QM, Miao ZL (2016) Landslide mapping from aerial photographs using change detection-based Markov random field. Remote Sens Environ 187:76–90. https://doi.org/10.1016/j.rse.2016.10.008

    Article  Google Scholar 

  • Li MH, Zhang L, Shi XG, Liao MS, Yang MS (2019) Monitoring active motion of the Guobu landslide near the Laxiwa hydropower station in China by time-series point-like targets offset tracking. Remote Sens Environ 221:80–93. https://doi.org/10.1016/j.rse.2018.11.006

    Article  Google Scholar 

  • Li M, Zhang L, Ding C, Li W, Luo H, Liao M, Xu Q (2020) Retrieval of historical surface displacements of the Baige landslide from time-series SAR observations for retrospective analysis of the collapse event. Remote Sens Environ 240:111695. https://doi.org/10.1016/j.rse.2020.111695

    Article  Google Scholar 

  • Liu XW, Chen Q, Zhao JJ, Xu Q, Luo R, Zhang YJ, Yang YH, Liu GX (2020) The spatial response pattern of coseismic landslides induced by the 2008 Wenchuan earthquake to the surface deformation and Coulomb stress change revealed from InSAR observations. Int J Appl Earth Obs Geoinf 87:102030. https://doi.org/10.1016/j.jag.2019.102030

    Article  Google Scholar 

  • Liu Z, Qiu HJ, Zhu YR, Liu Y, Yang DD, Ma SY, Zhang JJ, Wang YY, Wang LY, Tang BZ (2022) Efficient identification and monitoring of landslides by time-series InSAR combining single- and multi-look phases. Remote Sensing 14:1026. https://doi.org/10.3390/rs14041026

    Article  Google Scholar 

  • Lu Z, Dzurisin D, Biggs J, Wicks C and McNutt S (2010) Ground surface deformation patterns, magma supply, and magma storage at Okmok volcano, Alaska, from InSAR analysis: 1. Interruption deformation, 1997–2008. J Geophys Res-Sol Ea 115. https://doi.org/10.1029/2009jb006969

  • Lu CH, Ni CF, Chang CP, Yen JY and Chuang RY (2018) Coherence difference analysis of sentinel-1 SAR interferogram to identify earthquake-induced disasters in urban areas. Remote Sens-Basel 10https://doi.org/10.3390/rs10081318

  • Malenovsky Z, Rott H, Cihlar J, Schaepman ME, Garcia-Santos G, Fernandes R, Berger M (2012) Sentinels for science: potential of sentinel-1, -2, and -3 missions for scientific observations of ocean, cryosphere, and land. Remote Sens Environ 120:91–101. https://doi.org/10.1016/j.rse.2011.09.026

    Article  Google Scholar 

  • Meng Q, Li W, Raspini F, Xu Q, Peng Y, Ju Y, Zheng Y, Casagli N (2020) Time-series analysis of the evolution of large-scale loess landslides using InSAR and UAV photogrammetry techniques: a case study in Hongheyan, Gansu Province, Northwest China. Landslides 18:251–265. https://doi.org/10.1007/s10346-020-01490-8

    Article  Google Scholar 

  • Niu QF, Cheng WM, Liu Y, Xie YW, Lan HX, Cao YR (2012) Risk assessment of secondary geological disasters induced by the Yushu earthquake. J Mt Sci-Engl 9:232–242. https://doi.org/10.1007/s11629-012-2076-4

    Article  Google Scholar 

  • Pasquali P, Atzori S, Cantone A, Riccardi P, De Filippi M and Barbieri M (2012) Sarscape®, a commercial-off-the-shelf software package for the measurement, monitoring and modeling of geophysical phenomena. EAGE Workshop on Dead Sea Sinkholes–Causes, Effects and Solutions, European Association of Geoscientists & Engineers, pp cp-310–00013

  • Pu CH, Xu Q, Zhao KY, Jiang YN, Hao LN, Liu JL, Chen WL and Kou PL (2021) Characterizing the topographic changes and land subsidence associated with the mountain excavation and city construction on the Chinese loess plateau. Remote Sens-Basel 13https://doi.org/10.3390/rs13081556

  • Raucoules D, de Michele M, Malet JP, Ulrich P (2013) Time-variable 3D ground displacements from high-resolution synthetic aperture radar (SAR). Application to la Valette landslide (south french alps). Remote Sens Environ 139:198–204. https://doi.org/10.1016/j.rse.2013.08.006

    Article  Google Scholar 

  • Ren XM, Zhao WM, Chai CZ, Liu XJ (2002) Estimation of recurrent interval of strong earthquakes in ns earthquake belt. Inland Earthq 16:69–75 (in Chinese)

    Google Scholar 

  • Rodriguez E, Morris CS, Belz JE (2006) A global assessment of the SRTM performance. Photogramm Eng Remote Sens 72:249–260. https://doi.org/10.14358/Pers.72.3.249

    Article  Google Scholar 

  • Rosen PA, Hensley S, Joughin IR, Li FK, Madsen SN, Rodriguez E, Goldstein RM (2000) Synthetic aperture radar interferometry - invited paper. Proc IEEE 88:333–382. https://doi.org/10.1109/5.838084

    Article  Google Scholar 

  • Rosen P, Gurrola E, Agram PS, Sacco GF and Lavalle M (2015) The InSAR scientific computing environment (isce): a python framework for earth science. AGU Fall Meeting Abstracts, pp IN11C-1789

  • Rosenqvist A, Shimada M, Suzuki S, Ohgushi F, Tadono T, Watanabe M, Tsuzuku K, Watanabe T, Kamijo S, Aoki E (2014) Operational performance of the ALOS global systematic acquisition strategy and observation plans for ALOS -2 PALSAR-2. Remote Sens Environ 155:3–12. https://doi.org/10.1016/j.rse.2014.04.011

    Article  Google Scholar 

  • Samsonov SV, Trishchenko AP, Tiampo K, Gonzalez PJ, Zhang Y, Fernandez J (2014) Removal of systematic seasonal atmospheric signal from interferometric synthetic aperture radar ground deformation time series. Geophys Res Lett 41:6123–6130. https://doi.org/10.1002/2014gl061307

    Article  Google Scholar 

  • Sandwell D, Mellors R, Tong X, Wei M and Wessel P (2011) Gmtsar: an InSAR processing system based on generic mapping tools

  • Shan B, Zheng Y, Liu CL, Xie ZJ, Kong J (2017) Coseismic Coulomb failure stress changes caused by the 2017 m7.0 Jiuzhaigou earthquakes, and its relationship with the 2008 Wenchuan earthquake. Sci China Earth Sci 60:2181–2189. https://doi.org/10.1007/s11430-017-9125-2

    Article  Google Scholar 

  • Shao CJ, Li Y, Lan HX, Li PY, Zhou RJ, Ding HR, Yan ZK, Dong SL, Yan L, Deng T (2019) The role of active faults and sliding mechanism analysis of the 2017 Maoxian postseismic landslide in Sichuan, China. Bull Eng Geol Environ 78:5635–5651. https://doi.org/10.1007/s10064-019-01480-8

    Article  Google Scholar 

  • She J, Zhou X, Liu F, Cheng D and Liao L (2020) Preliminary results and analyses of post-earthquake geological hazards in Jiuzhaigou based on airborne lidar and imagery. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020: 541-545. 10.5194/isprs-archives-XLIII-B3-2020-541-2020

  • Shi XG, Zhang L, Tang MG, Li MH, Liao MS (2017) Investigating a reservoir bank slope displacement history with multi-frequency satellite SAR data. Landslides 14:1961–1973. https://doi.org/10.1007/s10346-017-0846-3

    Article  Google Scholar 

  • Sun J, Yu WD and Deng YK (2017) The SAR payload design and performance for the GF-3 mission. Sensors-Basel 17https://doi.org/10.3390/s17102419

  • Tanaka K, Nakayama M, Kanno M, Kimura H, Watanabe K, Hayashi Y, Asahi K, Watanabe T (2013) Aftercare for the prevention of a secondary health disaster in survivors of major earthquakes. Hypertens Res 36:759–761. https://doi.org/10.1038/hr.2013.75

    Article  Google Scholar 

  • Tang XW, Guo RM, Xu JQ, Sun HP, Chen XD, Zhou JC (2021) Probing the fault complexity of the 2017 ms 7.0 Jiuzhaigou earthquake based on the InSAR data. Remote Sens-Basel 13:1573. https://doi.org/10.3390/rs13081573

    Article  Google Scholar 

  • Torres R, Snoeij P, Geudtner D, Bibby D, Davidson M, Attema E, Potin P, Rommen B, Floury N, Brown M, Traver IN, Deghaye P, Duesmann B, Rosich B, Miranda N, Bruno C, L’Abbate M, Croci R, Pietropaolo A, Huchler M, Rostan F (2012) Gmes sentinel-1 mission. Remote Sens Environ 120:9–24. https://doi.org/10.1016/j.rse.2011.05.028

    Article  Google Scholar 

  • Transon J, d'Andrimont R, Maugnard A and Defourny P (2018) Survey of hyperspectral earth observation applications from space in the sentinel-2 context. Remote Sens-Basel 10https://doi.org/10.3390/rs10020157

  • Urgenson L, Schmidt AH, Combs J, Harrell S, Hinckley T, Yang Q, Ma Z, Yongxian L, Hongliang L, MacIver A (2014) Traditional livelihoods, conservation and meadow ecology in Jiuzhaigou national park, Sichuan, China. Hum Ecol Interdiscip J 42:481–491. https://doi.org/10.1007/s10745-014-9650-z

    Article  Google Scholar 

  • van Zyl JJ (2001) The shuttle radar topography mission (SRTM): a breakthrough in remote sensing of topography. Acta Astronaut 48:559–565. https://doi.org/10.1016/S0094-5765(01)00020-0

    Article  Google Scholar 

  • Walter D and Busch W (2012) Influences of dem quality parameters on the topographic phase correction in D-InSAR. 2012 IEEE International Geoscience and Remote Sensing Symposium, IEEE, pp 3927–3930

  • Wang Z (2008) A preliminary report on the great Wenchuan earthquake. Earthq Eng Eng Vib 7:225–234. https://doi.org/10.1007/s11803-008-0856-1

    Article  Google Scholar 

  • Wang T, Jonsson S (2015) Improved SAR amplitude image offset measurements for deriving three-dimensional coseismic displacements. IEEE J Sel Top Appl Earth Obs Remote Sens 8:3271–3278. https://doi.org/10.1109/Jstars.2014.2387865

    Article  Google Scholar 

  • Wang FT, Wang SX, Zhou Y, Wang LT, Yan FL, Li WJ, Liu XF (2016) High resolution remote sensing monitoring and assessment of secondary geological disasters triggered by the Lushan earthquake. Spectrosc Spect Anal 36:181–185. https://doi.org/10.3964/j.issn.1000-0593(2016)01-0181-05

    Article  CAS  Google Scholar 

  • Wang Y, Zhao B, Li J (2018) Mechanism of the catastrophic June 2017 landslide at Xinmo village, Songping river, Sichuan province, China. Landslides 15:333–345. https://doi.org/10.1007/s10346-017-0927-3

    Article  Google Scholar 

  • Wasowski J, Bovenga F (2014) Investigating landslides and unstable slopes with satellite multi temporal interferometry: current issues and future perspectives. Eng Geol 174:103–138. https://doi.org/10.1016/j.enggeo.2014.03.003

    Article  Google Scholar 

  • Werner C, Wegmüller U, Strozzi T and Wiesmann A (2000) Gamma SAR and interferometric processing software. Proceedings of the ers-envisat symposium, Gothenburg, Sweden, Citeseer, pp 1620

  • Werninghaus R, Buckreuss S (2010) The terrasar-x mission and system design. IEEE Trans Geosci Remote Sens 48:606–614. https://doi.org/10.1109/Tgrs.2009.2031062

    Article  Google Scholar 

  • Xu MZ, Wang ZY, Qi LJ, Liu L, Zhang K (2012) Disaster chains initiated by the Wenchuan earthquake. Environmental Earth Sciences 65:975–985. https://doi.org/10.1007/s12665-011-0905-3

    Article  Google Scholar 

  • Xu X, Wen X, Han Z, Chen G, Li C, Zheng W, Zhang S, Ren Z, Xu C, Tan X, Wei Z, Wang M, Ren J, He Z, Liang M (2013) Lushan m s7.0 earthquake: a blind reserve-fault event. Chin Sci Bull 58:3437–3443. https://doi.org/10.1007/s11434-013-5999-4

    Article  Google Scholar 

  • Xu W, Liu J, Xu G, Wang Y, Liu L and Shi P (2016) Earthquake disasters in china. Natural disasters in China, Springer, pp 37–72

  • Xu Q, Dong X and Li W (2019) Integrated space-air-ground early detection, monitoring and warning system for potential catastrophic geohazards. Geomatics and Information Science of Wuhan University 44: 957–966. https://doi.org/10.13203/j.whugis20190088 (in Chinese)

  • Yang F, Fan XM, Subramanian SS, Dou XY, Xiong JL, Xia B, Yu ZY and Xu Q (2021) Catastrophic debris flows triggered by the August 20 2019 rainfall, a decade since the Wenchuan earthquake, China. Landslides. https://doi.org/10.1007/s10346-021-01713-6

  • Yin YP, Cheng YL, Liang JT, Wang WP (2016) Heavy-rainfall-induced catastrophic rockslide-debris flow at Sanxicun, Dujiangyan, after the Wenchuan ms 8.0 earthquake. Landslides 13:9–23. https://doi.org/10.1007/s10346-015-0554-9

    Article  Google Scholar 

  • Yu QB, Wang Q, Yan XX, Yang TL, Song SY, Yao M, Zhou K, Huang XL (2020) Ground deformation of the Chongming east shoal reclamation area in shanghai based on SBAS-InSAR and laboratory tests. Remote Sens-Basel 12:1016. https://doi.org/10.3390/rs12061016

    Article  Google Scholar 

  • Zebker HA, Rosen PA, Hensley S (1997) Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps. J Geophys Res-Sol Ea 102:7547–7563. https://doi.org/10.1029/96jb03804

    Article  Google Scholar 

  • Zhang DX, Wang GH, Yang TJ, Zhang MC, Chen SH, Zhang FY (2013) Satellite remote sensing-based detection of the deformation of a reservoir bank slope in Laxiwa hydropower station, china. Landslides 10:231–238. https://doi.org/10.1007/s10346-012-0378-9

    Article  Google Scholar 

  • Zhang Y, Meng X, Dijkstra T, Jordan C, Chen G, Zeng R, Novellino A (2020) Forecasting the magnitude of potential landslides based on InSAR techniques. Remote Sens Environ 241:111738. https://doi.org/10.1016/j.rse.2020.111738

    Article  Google Scholar 

  • Zhao WY, You Y, Chen XQ, Liu JF, Chen JG (2020) Case study on debris-flow hazard mitigation at a world natural heritage site, Jiuzhaigou valley, western china. Geomat Nat Haz Risk 11:1782–1804. https://doi.org/10.1080/19475705.2020.1810784

    Article  Google Scholar 

  • Zuhlke M, Fomferra N, Brockmann C, Peters M, Veci L, Malik J and Regner P (2015) Snap (the sentinel application platform) and the ESA Sentinel 3 toolbox. Sentinel-3 for Science Workshop, 21

Download references

Acknowledgements

The authors thank the anonymous reviewers for their helpful suggestions to improve the paper.

Funding

The research was supported by the National Natural Science Foundation of China (U21A2032, 42077245) and the Second Tibetan Plateau Scientific Expedition and Research Program (STEP) (2019QZKK0902).

Author information

Authors and Affiliations

  1. State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China

    Ming Chang, Wenjing Sun, Hengzhi Xu & Liangliang Tang

Authors
  1. Ming Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wenjing Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hengzhi Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Liangliang Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Ming Chang: conceptualization, methodology; Wenjing SUN: supervision, editing; Hengzhi XU: data preparation, computational analysis; Liangliang TANG: investigation.

Corresponding author

Correspondence to Ming Chang.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Conflict of interest

The authors declare no competing interests.

Additional information

Responsible Editor: Philippe Garrigues

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chang, M., Sun, W., Xu, H. et al. Identification and deformation analysis of potential landslides after the Jiuzhaigou earthquake by SBAS-InSAR. Environ Sci Pollut Res 30, 39093–39106 (2023). https://doi.org/10.1007/s11356-022-25055-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-022-25055-5

Keywords

Search

Navigation